/* --------------------------------------------------------------------------
CppAD: C++ Algorithmic Differentiation: Copyright (C) 2003-17 Bradley M. Bell

CppAD is distributed under multiple licenses. This distribution is under
the terms of the
                    Eclipse Public License Version 1.0.

A copy of this license is included in the COPYING file of this distribution.
Please visit http://www.coin-or.org/CppAD/ for information on other licenses.
-------------------------------------------------------------------------- */

/*
$begin reverse_three.cpp$$
$spell
	Taylor
	Cpp
$$

$section Third Order Reverse Mode: Example and Test$$


$head Taylor Coefficients$$
$latex \[
\begin{array}{rcl}
	X(t) & = & x^{(0)} + x^{(1)} t + x^{(2)} t^2
	\\
	X^{(1)} (t) & = &  x^{(1)} + 2 x^{(2)} t
	\\
	X^{(2)} (t) & = &   2 x^{(2)}
\end{array}
\] $$
Thus, we need to be careful to properly account for the fact that
$latex X^{(2)} (0) = 2 x^{(2)}$$
(and similarly $latex Y^{(2)} (0) = 2 y^{(2)}$$).

$code
$srcfile%example/general/reverse_three.cpp%0%// BEGIN C++%// END C++%1%$$
$$

$end
*/
// BEGIN C++
# include <cppad/cppad.hpp>
namespace { // ----------------------------------------------------------
// define the template function cases<Vector> in empty namespace
template <typename Vector>
bool cases(void)
{	bool ok    = true;
	double eps = 10. * CppAD::numeric_limits<double>::epsilon();
	using CppAD::AD;
	using CppAD::NearEqual;

	// domain space vector
	size_t n = 2;
	CPPAD_TESTVECTOR(AD<double>) X(n);
	X[0] = 0.;
	X[1] = 1.;

	// declare independent variables and start recording
	CppAD::Independent(X);

	// range space vector
	size_t m = 1;
	CPPAD_TESTVECTOR(AD<double>) Y(m);
	Y[0] = X[0] * X[1];

	// create f : X -> Y and stop recording
	CppAD::ADFun<double> f(X, Y);

	// define x^0 and compute y^0 using user zero order forward
	Vector x0(n), y0(m);
	x0[0]    = 2.;
	x0[1]    = 3.;
	y0       = f.Forward(0, x0);

	// y^0 = F(x^0)
	double check;
	check    =  x0[0] * x0[1];
	ok      &= NearEqual(y0[0] , check, eps, eps);

	// define x^1 and compute y^1 using first order forward mode
	Vector x1(n), y1(m);
	x1[0] = 4.;
	x1[1] = 5.;
	y1    = f.Forward(1, x1);

	// Y^1 (x) = partial_t F( x^0 + x^1 * t )
	// y^1     = Y^1 (0)
	check = x1[0] * x0[1] + x0[0] * x1[1];
	ok   &= NearEqual(y1[0], check, eps, eps);

	// define x^2 and compute y^2 using second order forward mode
	Vector x2(n), y2(m);
	x2[0] = 6.;
	x2[1] = 7.;
	y2    = f.Forward(2, x2);

	// Y^2 (x) = partial_tt F( x^0 + x^1 * t + x^2 * t^2 )
	// y^2     = (1/2) *  Y^2 (0)
	check  = x2[0] * x0[1] + x1[0] * x1[1] + x0[0] * x2[1];
	ok    &= NearEqual(y2[0], check, eps, eps);

	// W(x)  = Y^0 (x) + 2 * Y^1 (x) + 3 * (1/2) * Y^2 (x)
	size_t p = 3;
	Vector dw(n*p), w(m*p);
	w[0] = 1.;
	w[1] = 2.;
	w[2] = 3.;
	dw   = f.Reverse(p, w);

	// check partial w.r.t x^0_0 of W(x)
	check = x0[1] + 2. * x1[1] + 3. * x2[1];
	ok   &= NearEqual(dw[0*p+0], check, eps, eps);

	// check partial w.r.t x^0_1 of W(x)
	check = x0[0] + 2. * x1[0] + 3. * x2[0];
	ok   &= NearEqual(dw[1*p+0], check, eps, eps);

	// check partial w.r.t x^1_0 of W(x)
	check = 2. * x0[1] + 3. * x1[1];
	ok   &= NearEqual(dw[0*p+1], check, eps, eps);

	// check partial w.r.t x^1_1 of W(x)
	check = 2. * x0[0] + 3. * x1[0];
	ok   &= NearEqual(dw[1*p+1], check, eps, eps);

	// check partial w.r.t x^2_0 of W(x)
	check = 3. * x0[1];
	ok   &= NearEqual(dw[0*p+2], check, eps, eps);

	// check partial w.r.t x^2_1 of W(x)
	check = 3. * x0[0];
	ok   &= NearEqual(dw[1*p+2], check, eps, eps);

	return ok;
}
} // End empty namespace
# include <vector>
# include <valarray>
bool reverse_three(void)
{	bool ok = true;
	ok &= cases< CppAD::vector  <double> >();
	ok &= cases< std::vector    <double> >();
	ok &= cases< std::valarray  <double> >();
	return ok;
}
// END C++
